Centralized photovoltaic power station site selection method and system based on game theory

Abstract

The invention provides a centralized photovoltaic power station site selection method and system based on a game theory. The scheme comprises the following steps: acquiring multi-source index factors influencing photovoltaic power station site selection in each to-be-selected region in a preset region and related data thereof; weighting each index factor by adopting an index factor weighting strategy based on a game theory thought based on the obtained index factors and related data thereof; and based on the obtained related data corresponding to each index factor of the to-be-selected region and the weighting result of each index factor, calculating to obtain a suitability score of the photovoltaic power station planned in the to-be-selected region, and based on the scoring result, realizing the site selection of the photovoltaic power station. The problem that a traditional scheme is difficult to comprehensively and systematically reflect actual requirements of photovoltaic power station construction, the importance degree of different index factors cannot be effectively measured, the importance degree of each index factor cannot be effectively highlighted in the photovoltaic power station site selection process, and then the accuracy of a selection result is insufficient, and the selection efficiency is improved is effectively solved. And actual requirements cannot be met.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic power station site selection, and in particular relates to a centralized photovoltaic power station site selection method and system based on game theory. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Site selection is an important early stage in the construction of a photovoltaic power station. The quality of site selection is directly related to the construction cost of the photovoltaic power station, the power generation efficiency after completion, and the impact on the local ecosystem. It plays a decisive role in the success or failure of the entire photovoltaic power generation project.

[0004] Traditional photovoltaic power station site selection schemes generally adopt a combination of geographic information system (GIS) and a variety of evaluation methods, such as multi-factor evaluation (MCE), entropy weight method, analytic hierarchy process (AHP, FAHP), Delphi method and comprehensive evaluation method. By comparing the influence of various influencing factors on the suitability of centralized photovoltaic power station construction, the weight ratio of each factor is calculated, so as to obtain the regional suitability evaluation based on the site selection of the power station. The inventor found that the suitability of photovoltaic power station site selection needs to consider factors at multiple levels, including but not limited to social impact, economic benefits, terrain conditions and ecological environmental protection. The comprehensive consideration of these factors is aimed at ensuring that the construction of photovoltaic power stations can not only promote local economic development, but also minimize the negative impact on the environment. However, the traditional single evaluation method is often highly subjective and it is difficult to fully and systematically reflect the actual needs of photovoltaic power station construction, resulting in insufficient accuracy of photovoltaic power station site selection results and unable to meet actual needs; secondly, although some comprehensive evaluation schemes involve multiple indicator factors, they do not effectively measure the importance of different indicator factors. The importance of each indicator factor cannot be effectively highlighted in the process of photovoltaic power station site selection, which leads to insufficient accuracy of the selection results and cannot meet actual needs. Summary of the invention

[0005] The embodiment of the present invention provides a centralized photovoltaic power station site selection method and system based on game theory to solve the problem that traditional solutions usually adopt a single evaluation method which is often highly subjective and difficult to comprehensively and systematically reflect the actual needs of photovoltaic power station construction, and that although some comprehensive evaluation methods involve different evaluation index factors, they do not effectively measure the importance of different index factors. The importance of each index factor cannot be effectively highlighted in the photovoltaic power station site selection process, which leads to the problem that the selection result is not accurate enough and cannot meet the actual needs.

[0006] According to a first aspect of an embodiment of the present invention, a method for selecting a site for a centralized photovoltaic power station based on game theory is provided, comprising:

[0007] Obtain multi-source index factors and related data that affect the site selection of photovoltaic power stations in each candidate area within the preset area;

[0008] Based on the obtained indicator factors and their related data, an indicator factor weighting strategy based on game theory is used to weight each indicator factor; wherein, the indicator factor weighting strategy is specifically as follows: weighting each indicator factor based on fuzzy analytic hierarchy process to obtain a first weight vector; based on the obtained related data of each indicator factor, using entropy weight method combined with approximate ideal solution sorting method to weight each indicator data to obtain a second weight vector; based on the obtained first weight vector and second weight vector, weight fusion is performed through game theory to obtain a weight vector that integrates subjective opinions and objective information;

[0009] Based on the obtained relevant data corresponding to each indicator factor of the candidate area and the weighted results of each indicator factor, the suitability score of the planned photovoltaic power station in the candidate area is calculated, and the site selection of the photovoltaic power station is realized based on the score result.

[0010] Furthermore, the entropy weight method is combined with the approximate ideal solution sorting method to assign weights to each indicator data to obtain a second weight vector, specifically: standardizing the relevant data of each indicator factor obtained; calculating the indicator weight matrix based on the relevant data of each indicator factor after standardization; calculating the information entropy and the indicator difference coefficient based on the indicator weight matrix; and determining the weight of each indicator factor based on the obtained information entropy and indicator difference coefficient.

[0011] Furthermore, based on the obtained first weight vector and the second weight vector, weight fusion is performed through the idea of ​​game theory to obtain a weight vector that integrates subjective opinions and objective information. Specifically, based on the obtained first weight vector and the second weight vector, the fused weight vector is obtained by weighted summation; wherein, in the fusion process, the weights in the weighted process of the first weight vector and the second weight vector are determined based on the idea of ​​game theory.

[0012] Furthermore, the indicator factors include geographic data, population distribution data, solar radiation data and land cover type.

[0013] Furthermore, the solution not only considers the adaptability of the photovoltaic power station in the site selection of the photovoltaic power station, but also imposes restrictions on the restricted area, and the site selection planning of the photovoltaic power station is not carried out in the restricted area.

[0014] Furthermore, restricted area constraints are imposed on the selected areas, and the restricted area constraints include: setting areas with an altitude exceeding a preset height as restricted areas; setting areas with a slope exceeding a preset angle as restricted areas; setting natural environment protection areas, farmlands, factory areas and urban construction areas as restricted areas; and not conducting photovoltaic power station site planning for the restricted areas.

[0015] Furthermore, the site selection of the photovoltaic power station is realized based on the scoring results, specifically: based on the suitability score of each candidate area in the preset area, the adaptability of each candidate area is graded after eliminating the restricted area, an interface is displayed based on the grading results, and the optimal photovoltaic power station site selection result is determined from the display interface.

[0016] According to a second aspect of an embodiment of the present invention, a centralized photovoltaic power station site selection system based on game theory is provided, comprising:

[0017] A data acquisition unit, which is used to acquire multi-source index factors and related data that affect the site selection of photovoltaic power stations in each candidate area within a preset area;

[0018] A weight calculation unit is used to weight each indicator factor based on the obtained indicator factors and related data thereof, using an indicator factor weighting strategy based on the idea of ​​game theory; wherein the indicator factor weighting strategy is specifically as follows: weighting each indicator factor based on the fuzzy analytic hierarchy process to obtain a first weight vector; based on the obtained related data of each indicator factor, using the entropy weight method combined with the approximate ideal solution sorting method to weight each indicator data to obtain a second weight vector; based on the obtained first weight vector and the second weight vector, weight fusion is performed through the idea of ​​game theory to obtain a weight vector that integrates subjective opinions and objective information;

[0019] The site selection unit is used to calculate the suitability score of the photovoltaic power station planned in the candidate area based on the relevant data corresponding to each indicator factor of the candidate area and the weighted results of each indicator factor, and realize the site selection of the photovoltaic power station based on the score result.

[0020] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, comprising a memory, a processor, and a computer program stored and running on the memory, wherein when the processor executes the program, the method for selecting a site for a centralized photovoltaic power station based on game theory is implemented.

[0021] According to a fourth aspect of an embodiment of the present invention, a non-transitory computer-readable storage medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method for selecting a site for a centralized photovoltaic power station based on game theory is implemented.

[0022] One or more of the above technical solutions have the following beneficial effects:

[0023] (1) The present invention provides a centralized photovoltaic power station site selection method and system based on game theory. The scheme is based on the idea of ​​game theory, adopts multi-source data to select evaluation indicators, and performs comprehensive weight calculation based on fuzzy hierarchical analysis method and entropy weight-approximate ideal solution sorting method combined with game theory. By adding the weighted sum of the relevant data of each indicator factor, the suitability score of the construction of different areas of the centralized photovoltaic power station is generated, which effectively solves the problem that multiple indicator factors cannot be effectively utilized due to the influence of complex factors in the site selection of photovoltaic power stations, can realize scientific and accurate site selection evaluation of photovoltaic power stations, and has good applicability.

[0024] (2) The scheme establishes a photovoltaic site suitability evaluation system by integrating multi-source data and empowering methods. This system can provide specific suitability recommendations and implementation strategies for different regions in the early stages of photovoltaic project planning, which can significantly improve the accuracy and efficiency of photovoltaic site selection.

[0025] (3) The scheme introduces restricted area constraints and pre-excludes restricted areas, which can effectively improve the efficiency of photovoltaic site selection and meet actual needs.

[0026] Advantages of additional aspects of the present invention will be given in part in the following description, and in part will become obvious from the following description, or will be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 It is a flow chart of a method for site selection of a centralized photovoltaic power station based on game theory described in an embodiment of the present invention;

[0029] Figure 2 The preset area related data described in the embodiment of the present invention;

[0030] Figure 3 This is a schematic diagram of the 0.1-0.9 scaling method described in an embodiment of the present invention;

[0031] Figure 4 A schematic diagram of a fuzzy hierarchical analysis method judgment matrix described in an embodiment of the present invention;

[0032] Figure 5 Schematic diagram of calculation results of the entropy weight-Tops is method described in an embodiment of the present invention;

[0033] Figure 6A schematic diagram of the comprehensive weight obtained based on the idea of ​​game theory in an embodiment of the present invention;

[0034] Figure 7 The distribution of altitude restriction zones described in the embodiment of the present invention;

[0035] Figure 8 The distribution of the slope restriction area described in the embodiment of the present invention;

[0036] Fig. 9 The distribution of restricted areas of land cover types described in the embodiment of the present invention;

[0037] Fig.10 A distribution map of the suitability of the construction of a centralized photovoltaic power station as described in an embodiment of the present invention;

[0038] Fig.11 It is a schematic diagram of the proportion of suitable areas in the whole country and each province described in the embodiment of the present invention. DETAILED DESCRIPTION

[0039] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0040] It should be noted that the terms used herein are for describing specific embodiments only and are not intended to be limiting of exemplary embodiments according to the present invention.

[0041] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0042] like Figure 1 As shown, the embodiment of the present invention provides a centralized photovoltaic power station site selection method based on game theory, which specifically includes the following processing procedures:

[0043] Step 1: Obtain multi-source index factors and related data that affect the site selection of photovoltaic power stations in each candidate area within the preset area;

[0044] In a specific implementation, the indicator factors include geographic data, population distribution data, solar radiation data, and land cover type;

[0045] The data sources for obtaining the index factor-related data include the ERA5-Land reanalysis dataset, MCD12Q1 land cover product, NASADEM_HGT, and Population Counts population distribution dataset; the total solar radiation data is calculated based on the ERA5-Land reanalysis dataset, and the slope and aspect data are obtained through NASADEM_HGT calculation to obtain several index data, such as Figure 2 As shown, it can be understood that the solution described in this embodiment is not limited to a specific preset area, and the solution can be applied to different areas.

[0046] In more implementations, it is necessary to perform data preprocessing on the acquired indicator factor related data, and specifically perform the following processing process:

[0047] Preprocess the relevant data of each indicator factor, including the unification of data benchmarks and image cropping. In order to ensure that different data can be superimposed and integrated, a unified benchmark data is used to uniformly sample and crop multi-source data. Since multi-source data has different measurement units and different numerical ranges, it is not directly comparable. It is also necessary to standardize and grade all multi-source data. The automatic breakpoint method is used to unify the data into 1 to 10 levels. The level represents the degree of influence of the data on the suitability of the construction of photovoltaic power stations.

[0048] Step 2: Based on the obtained indicator factors and their related data, the indicator factor weighting strategy based on the game theory is used to weight each indicator factor; wherein the indicator factor weighting strategy is specifically as follows: weighting each indicator factor based on the fuzzy analytic hierarchy process to obtain a first weight vector; based on the obtained related data of each indicator factor, the entropy weight method is combined with the approximate ideal solution sorting method to weight each indicator data to obtain a second weight vector; based on the obtained first weight vector and the second weight vector, weight fusion is performed through the game theory to obtain a weight vector that integrates subjective opinions and objective information;

[0049] In a specific implementation, the step 2 specifically includes the following processing steps:

[0050] Step 201: weighting each indicator data based on FAHP fuzzy analytic hierarchy process;

[0051] FAHP is a multi-criteria decision-making method that performs quantitative analysis on qualitative problems. The degree of people's cognition of objective things is expressed by fuzzy numbers, which overcomes the difficulty of consistency test of analytic hierarchy process (AHP) and expands the scope of application. The fuzzy analytic hierarchy process model includes target layer, criterion layer and decision layer, among which:

[0052] The target layer includes one target, which is to evaluate the suitability of the construction of a centralized PV power station;

[0053] The criterion layer includes 6 criteria: total solar radiation criterion, sunshine stability criterion, land cover type criterion, slope aspect criterion, slope criterion, and population distribution criterion; the decision layer is to form different schemes according to the suitability results. There is no requirement for the decision layer in the scheme described in this embodiment, so it will not be repeated here.

[0054] Specifically, the weighting process through FAHP fuzzy analytic hierarchy process includes the following processing:

[0055] First, quantitative expression is performed by comparing the relative importance of indicator factors, using a 0.1 to 0.9 scale (e.g. Figure 3 The relative importance of the comparison criteria data is quantitatively scaled to obtain the fuzzy complementary judgment matrix A = (a ij )n×n(such as Figure 4 As shown in the figure, the larger the value, the more important it is. Then according to the matrix element a ij The indicator weights of matrix A are calculated using the number of indicators n.

[0056]

[0057] Among them, W i is the weight of the indicator factor, and W i ≥0(i∈n). In order to judge the reasonable consistency of the calculated weights, a consistency test based on the compatibility index I(A,W) is also required. The characteristic matrix W is calculated based on the index weights = (w ij )n×n elements, and then calculate the compatibility to determine whether it is satisfactory consistency.

[0058]

[0059] If the compatibility index value is less than a specific threshold value α (α = 0.1), the judgment matrix is ​​considered to be a satisfactory consistency matrix. The calculated value α = 0.0729 indicates that the judgment matrix is ​​at a reasonable consistency level, otherwise the judgment matrix needs to be reconstructed.

[0060] Step 202: weighting each indicator factor based on the entropy weight-TOPSIS method (i.e., the approach to ideal solution ranking method);

[0061] The entropy weight-TOPSIS method is a multi-attribute decision-making method that combines the entropy weight method and the TOPS IS method. This method firstly objectively determines the weight of each evaluation index through the entropy weight method, and uses information entropy to measure the amount of information of each index, thereby giving greater weight to the index with higher importance; then, the TOPSIS method is used to calculate the distance of each scheme to the ideal solution and the negative ideal solution, and the schemes are ranked by relative proximity. Through this comprehensive evaluation method, the optimal scheme can be identified more scientifically and objectively, and the accuracy and reliability of decision-making can be improved.

[0062] In the specific implementation, the entropy weight-TOPSIS method weighting includes the following processing:

[0063] First, the original data X(x ij)m×n are standardized to make them comparable under the same dimension. Generally, corresponding adjustments (non-negative translation) are made to avoid unreasonable data. First, the index weight matrix P is calculated for the processed data. ij , and then calculate the information entropy E j (e j ) and the index difference coefficient d j , respectively reflecting the information disorder and order of the j-th indicator.

[0064]

[0065] d j =1-e j (6)

[0066] Then calculate the weight T of each indicator according to the proportion of column elements j , construct the weighted normalization matrix V(m×n). In order to eliminate the influence of data dimension, we need to normalize the data. Then calculate the positive ideal solution A+(v ij (max)) and the negative ideal solution A-(v ij (min)) construct the optimal distance matrix M (m×n) and the worst distance matrix N (m×n), and then calculate the distance D+ and D- between each evaluation object and the solution. Finally, the closeness C of each solution index to the ideal solution is obtained. j ( Figure 5 ), the greater the degree of closeness, the better the indicator and the greater the corresponding weight.

[0067]

[0068] v ij =x ij × j (8)

[0069]

[0070] Step 203: Comprehensively analyze the weight of each indicator data based on game theory

[0071] FAHP fuzzy analytic hierarchy process is a subjective weighting method. The weights it obtains reflect the subjective experience and judgment of decision makers. The relative importance of each factor is usually more reliable, but the accuracy and reliability of the weighting results are often questioned. In comparison, the entropy weight Topsis method relies on objective data to allocate weights, and the weight coefficients of each factor are calculated through accurate data. The weighting results are more mathematically based, but the disadvantage is that it only focuses on objective data. Considering the above situation, the game theory idea is used to calculate the FAHP fuzzy analytic hierarchy process and the entropy weight Topsis method, and the weight results that take into account both subjective opinions and objective information are obtained. The weights of the two methods are linearly combined to obtain the combined weight.

[0072] W=β 1 W j +β 2 T j (12)

[0073] Among them, W j is the weighted result of FAHP fuzzy analytic hierarchy process, T j is the weighted result of entropy weight Topsis method, β 1 and β 2 is the weight coefficient.

[0074] Use game theory to find the Nash equilibrium point (Formula 13), where G 1 =W j ,G 2 =T j The formula is derived as follows to calculate the optimal solution and then obtain the optimal weight coefficients β1 and β2. The weight coefficients are normalized to P1 and P2, and finally the final comprehensive weight result P*( Figure 6 ).

[0075] min‖β 1 W j +β 2 T j -G q ‖ 2 q=1,2 (13)

[0076]

[0077] P * =P 1 W j +P 2 T j (15)

[0078] Step 3: Based on the relevant data corresponding to each indicator factor of the candidate area and the weighted results of each indicator factor, calculate the suitability score of the planned photovoltaic power station in the candidate area; and realize the site selection of the photovoltaic power station based on the score result.

[0079] In more implementations, the solution not only considers the adaptability of the photovoltaic power station in the site selection of the photovoltaic power station, but also performs restriction area constraints, and the photovoltaic power station site selection planning is not performed in the restricted area.

[0080] In more embodiments, restricted area constraints are imposed on the selected area, and the restricted area constraints include: setting the area with an altitude exceeding a preset height as a restricted area; setting the area with a slope exceeding a preset angle as a restricted area; setting natural environment protection areas, farmlands, factory areas and urban construction areas as restricted areas; and not performing photovoltaic power station site planning for the restricted areas.

[0081] In one or more embodiments, the site selection of the photovoltaic power station is achieved based on the scoring results, specifically: based on the suitability scores of each candidate area in the preset area, each candidate area is graded for adaptability after removing the restricted area, an interface is displayed based on the grading results, and the optimal photovoltaic power station site selection result is determined from the display interface.

[0082] Specifically, considering the restrictions on the construction of photovoltaic power stations under certain circumstances, the areas that do not meet the conditions for the construction of centralized photovoltaic power stations are marked separately by setting up restricted areas, making the site selection planning of centralized photovoltaic power stations more reasonable and complete. Due to the limitations of the current level of photovoltaic power station construction technology and the practical difficulties of building centralized photovoltaic power stations in high-altitude areas, areas with an altitude of more than 5,000 meters are set as restricted areas. Figure 7 Considering the terrain conditions for building centralized photovoltaic power stations in mountainous areas, areas with slopes exceeding 50° are set as restricted areas. Figure 8 Based on the principles of ecological and environmental protection and the requirements for the soil type of construction land, permanent wetlands, snow and ice, water, forests, farmlands, factory areas, and urban construction areas are set as restricted areas. Fig. 9 .

[0083] In addition, the processed classification data is used to evaluate the suitability of photovoltaic power station construction based on the calculated subjective and objective comprehensive weight coefficients to obtain the suitability score of centralized photovoltaic power stations, which can reflect the suitability of building centralized photovoltaic power stations across the country. However, the complicated score data is not conducive to people's interpretation of the distribution situation, and the suitability score map is slightly flawed in terms of intuitiveness and visualization. To solve the above problems, for the suitability score map of centralized photovoltaic power station construction, the suitability is divided with 4.5, 6.5, and 8.5 as thresholds, and the restricted areas where centralized photovoltaic power stations cannot be built are eliminated. The national scope is divided into four levels: restricted area, low suitability, relatively suitable, suitable, and high suitability, which intuitively presents the distribution of various types of suitability. Fig.10 Through the distribution of suitability, we can get the proportion of suitable areas in the whole country and each province. Fig.11 , presenting the suitability evaluation results of centralized photovoltaic power station construction in my country, which can provide reference value for the preliminary site selection of centralized photovoltaic power stations in my country, and then put forward some countermeasures and suggestions for the promotion of photovoltaic power generation projects in my country.

[0084] In one or more implementations, with respect to the above method, this embodiment provides a centralized photovoltaic power station site selection system based on game theory according to a second aspect of an embodiment of the present invention, including:

[0085] A data acquisition unit, which is used to acquire index factors and related data that affect the site selection of a photovoltaic power station in a candidate area;

[0086] A weight calculation unit is used to weight each indicator factor based on the obtained indicator factors and related data thereof, using an indicator factor weighting strategy based on the idea of ​​game theory; wherein the indicator factor weighting strategy is specifically as follows: weighting each indicator factor based on the fuzzy analytic hierarchy process to obtain a first weight vector; based on the obtained related data of each indicator factor, using the entropy weight method combined with the approximate ideal solution sorting method to weight each indicator data to obtain a second weight vector; based on the obtained first weight vector and the second weight vector, weight fusion is performed through the idea of ​​game theory to obtain a weight vector that integrates subjective opinions and objective information;

[0087] The site selection unit is used to calculate the suitability score of the photovoltaic power station planned in the candidate area based on the relevant data corresponding to each indicator factor of the candidate area and the weighted results of each indicator factor, and realize the site selection of the photovoltaic power station based on the score result.

[0088] It can be understood that the system described in this embodiment corresponds to the method described in the above embodiment, and its technical details have been described in detail in Embodiment 1 and will not be repeated here.

[0089] In further embodiments, there is also provided:

[0090] An electronic device includes a memory and a processor and computer instructions stored in the memory and executed on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the above embodiment. For the sake of brevity, no further description is given here.

[0091] It should be understood that in this embodiment, the processor may be a central processing unit CPU, and the processor may also be other general-purpose processors, digital signal processors DSP, application-specific integrated circuits ASIC, off-the-shelf programmable gate arrays FPGA or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0092] The memory may include a read-only memory and a random access memory, and provide instructions and data to the processor. A portion of the memory may also include a non-volatile random access memory. For example, the memory may also store information about the device type.

[0093] A computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the method described in the above embodiment is completed.

[0094] The method in the above embodiment can be directly embodied as being executed by a hardware processor, or can be executed by a combination of hardware and software modules in the processor. The software module can be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware. To avoid repetition, it will not be described in detail here.

[0095] Those skilled in the art will appreciate that the units, i.e., algorithm steps, of the various examples described in the present embodiment can be implemented in electronic hardware or in a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0096] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A centralized photovoltaic power station site selection method based on game theory, characterized in that: include: Obtain multi-source index factors and related data that affect the site selection of photovoltaic power stations in each candidate area within the preset area; Based on the obtained indicator factors and their related data, an indicator factor weighting strategy based on game theory is used to weight each indicator factor; wherein, the indicator factor weighting strategy is specifically as follows: weighting each indicator factor based on fuzzy analytic hierarchy process to obtain a first weight vector; based on the obtained related data of each indicator factor, using entropy weight method combined with approximate ideal solution sorting method to weight each indicator data to obtain a second weight vector; based on the obtained first weight vector and second weight vector, weight fusion is performed through game theory to obtain a weight vector that integrates subjective opinions and objective information; Based on the obtained relevant data corresponding to each indicator factor of the candidate area and the weighted results of each indicator factor, the suitability score of the planned photovoltaic power station in the candidate area is calculated, and the site selection of the photovoltaic power station is realized based on the score result.

2. The method for selecting a centralized photovoltaic power station site based on game theory according to claim 1, characterized in that: The entropy weight method is combined with the approximate ideal solution sorting method to assign weights to each indicator data to obtain a second weight vector, specifically: standardizing the relevant data of each indicator factor obtained; calculating the indicator weight matrix based on the relevant data of each indicator factor after standardization; calculating the information entropy and the indicator difference coefficient based on the indicator weight matrix; and determining the weight of each indicator factor based on the obtained information entropy and the indicator difference coefficient.

3. The method for selecting a site for a centralized photovoltaic power station based on game theory according to claim 1, characterized in that: Based on the obtained first weight vector and the second weight vector, weight fusion is performed through the idea of ​​game theory to obtain a weight vector that integrates subjective opinions and objective information. Specifically, based on the obtained first weight vector and the second weight vector, the fused weight vector is obtained by weighted summation; wherein, in the fusion process, the weights in the weighted process of the first weight vector and the second weight vector are determined based on the idea of ​​game theory.

4. The method for selecting a site for a centralized photovoltaic power station based on game theory according to claim 1, characterized in that: The indicator factors include geographic data, population distribution data, solar radiation data and land cover type.

5. The method for selecting a site for a centralized photovoltaic power station based on game theory according to claim 1, characterized in that: The solution not only considers the adaptability of the photovoltaic power station in the site selection of the photovoltaic power station, but also imposes restrictions on the restricted area, and the site selection planning of the photovoltaic power station is not carried out in the restricted area.

6. The method for selecting a site for a centralized photovoltaic power station based on game theory as claimed in claim 5, characterized in that: Restricted area constraints are imposed on the selected areas, and the restricted area constraints include: setting areas with an altitude exceeding a preset height as restricted areas; setting areas with a slope exceeding a preset angle as restricted areas; setting natural environment protection areas, farmlands, factory areas and urban construction areas as restricted areas; and not conducting photovoltaic power station site planning for the restricted areas.

7. The method for selecting a site for a centralized photovoltaic power station based on game theory according to claim 1, characterized in that: The site selection of the photovoltaic power station based on the scoring results is specifically as follows: based on the suitability scores of each candidate area in the preset area, each candidate area is graded for adaptability after removing the restricted area, an interface is displayed based on the grading results, and the optimal photovoltaic power station site selection result is determined from the display interface.

8. A centralized photovoltaic power station site selection system based on game theory, characterized in that: include: A data acquisition unit, which is used to acquire the index factors and related data that affect the site selection of the photovoltaic power station in the selected area; A weight calculation unit is used to weight each indicator factor based on the obtained indicator factors and related data thereof, using an indicator factor weighting strategy based on the idea of ​​game theory; wherein the indicator factor weighting strategy is specifically as follows: weighting each indicator factor based on the fuzzy analytic hierarchy process to obtain a first weight vector; based on the obtained related data of each indicator factor, using the entropy weight method combined with the approximate ideal solution sorting method to weight each indicator data to obtain a second weight vector; based on the obtained first weight vector and the second weight vector, weight fusion is performed through the idea of ​​game theory to obtain a weight vector that integrates subjective opinions and objective information; The site selection unit is used to calculate the suitability score of the planned photovoltaic power station in the candidate area based on the relevant data corresponding to each indicator factor of the candidate area and the weighted results of each indicator factor, and realize the site selection of the photovoltaic power station based on the score result.

9. An electronic device comprising a memory, a processor and a computer program stored and running on the memory, characterized in that: When the processor executes the program, the method for site selection of a centralized photovoltaic power station based on game theory as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, a centralized photovoltaic power station site selection method based on game theory is implemented as described in any one of claims 1 to 7.

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